The traditional approach to manufacturing quality assurance involves the following activities: (1) control materials, (2) write specifications, (3) train operators, (4) maintain equipment, (5) set and control knob settings, and (6) check part quality through exhaustive final inspection and occasional metallurgical cutups. In the traditional approach, the manufacturing process itself is assumed to be repeatable. Directly monitoring the real-time response of the machine tool or the manufacturing process is not considered.
The in-process approach to manufacturing quality assurance extends the traditional approach by including a verification stage and modifying the post-process inspection stage, thus resulting in the following activities: (1) control materials, (2) write specifications, (3) train operators, (4) maintain equipment, (5) set and control knob settings, (6) verify that the manufacturing process is repeatable by interrogating the real-time response, (7) reduce dependence on final inspection as the database of in-process signatures for “good” welds evolves and matures, and (8) perform metallurgical cutups only as necessary.
Assumptions result in unnecessary risks. InnerVoice eliminates the blind spot in the traditional approach to manufacturing quality assurance by continuously interrogating the process performance through the use of powerful, real-time data analytics. InnerVoice captures a unique digital fingerprint of the manufacturing process on a part-by-part basis searching for outliers with novel or anomalous process behavior. Instead of allowing potentially flawed components from receiving additional downstream, value-added operations, these "suspect" parts are removed from production to undergo further quality control scrutiny thereby creating a "inspect for cause" methodology.
Please contact us for a no-obligation consultation to learn how InnerVoice can help migrate your traditional quality assurance approach to an in-process approach.